Doctoral Dissertation Research: Examining Diet, Mobility, and Social Dynamics Using a Multi Isotopic Approach and GIS

该奖项的全部或部分资金来自《2021年美国救援计划法案》(公法117-2)。纵观人类历史，许多因素影响了个人的流动性和饮食，在许多情况下，饮食习惯随着社会地位和信仰体系等其他因素的变化而发生变化。使用生物考古学研究方法，将骨骼分析与环境和文化方面相结合，在人口和个人层面上检查饮食和埋葬方式，这项博士论文研究考察了社会重组如何影响过去人类人口中更广泛的社区。探索生前的饮食选择和死后的状态，可以增进人们对食物和埋葬习俗如何与社会角色相关的知识，并重申社会角色。该项目的更广泛影响包括对一名女研究生的STEM培训，加强国际科学研究合作，以及向公众传播研究成果。该项目探索信仰体系和社会地位与饮食、起源和流动性的关系。研究人员考虑了来自同一社区的两个骨骼样本的年龄、性别和地位，这些样本分别代表宗教精英和非精英个人。这项研究检查了是否存在基于潜在地位差异的饮食差异，以及是否可以为非本地个人确定出生地。该项目结合了生物化学、地理空间和统计学方法，包括四个同位素判别式(碳、氮、氧和锶)、贝叶斯水果混合模型和研究区域的地理空间分析。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). Throughout human history, many factors have influenced an individual’s mobility and diet, and in many cases, dietary practices have diverged alongside changes in other factors such as social status and belief systems. Using bioarchaeological research methods that combine skeletal analyses with aspects of environment and culture to examine diet and burial style at the population and individual levels, this doctoral dissertation research examines how social reorganization affected a broader community in past human populations. Exploring dietary choices during life and status after death advances knowledge about how food and burial practices relate to and reaffirm social roles. Broader impacts of the project include STEM training of a female graduate student, strengthening of international scientific research collaborations, and dissemination of research to the public.The project explores the relationship of belief systems and social status to diet, origins, and mobility. The investigators consider these dynamics in conjunction with age, sex, and status for two skeletal samples representing religious elites and non-elite individuals, respectively, from the same community. The research examines whether there are dietary differences based on potential status differences and whether place of origin can be identified for non-local individuals. The project utilizes a combination of biochemical, geospatial, and statistical methods, including four isotopic discriminants (carbon, nitrogen, oxygen, and strontium), the Bayesian FRUITS mixing model, and geospatial analysis of the study region.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.